Merge branch 'main' into docs/fix-documentation-typos

Author: fm1320

docs/articles/hybrid_search_&_rerank_rag.md

@@ -1,5 +1,8 @@
 # Optimizing RAG with Hybrid Search & Reranking
 
+> **Scaling RAG to production is *very* painful.**  
+> Hybrid search, reranking, latency, and cost add up quickly. Let us help you simplify it. → **[Talk to us here](https://getdemo.superlinked.com/?utm_source=opt_rag)**
+
 Retrieval-Augmented Generation (RAG) is revolutionizing traditional search engines and AI methodologies for information retrieval. However, standard RAG systems employing simple semantic search often lack efficiency and precision when dealing with extensive data repositories. Hybrid search, on the other hand, combines the strengths of different search methods, unlocking new levels of efficiency and accuracy. **Hybrid search is flexible and can be adapted to tackle a wider range of information needs**.
 
 Hybrid search can also be paired with **semantic reranking** (to reorder outcomes) to further enhance performance. Combining hybrid search with reranking holds immense potential for various applications, including natural language processing tasks like question answering and text summarization, even for implementation at a large-scale.
@@ -372,3 +375,4 @@ We've looked at how RAG system performance can be enhanced by using hybrid searc
 - [Ashish Abraham, author](https://www.linkedin.com/in/ashish-abraham-811a23201/)
 - [Mór Kapronczay, contributor](https://www.linkedin.com/in/mór-kapronczay-49447692)
 - [Robert Turner, editor](https://robertturner.co/copyedit)
+

docs/articles/real_estate_nlq_agent.md

@@ -719,3 +719,9 @@ Well before ending this one, there are couple of points I want your attention. S
 The most important one here is that I intentionally gave more weight to the Price rather than other filters when we were creating the query, as It acts as a hard constraint, while other attributes like location or amenities adjust the relevance within that boundary. I mean the Price is the most important factor I guess when we are looking out for the real estate.
 
 And as I said earlier, our NLQ engine doesn’t depends on the structured filters, instead it understand the natural language directly.
+
+---
+## Contributors
+
+- [Vipul Maheshwari, author](https://www.linkedin.com/in/vipulmaheshwarii/)
+- [Filip Makraduli, reviewer](https://www.linkedin.com/in/filipmakraduli/)

docs/tools/vdb_table/data/activeloop.json

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